RESOURCE ALLOCATION IN MULTIUSER MULTICARRIER WIRELESS SYSTEMS RESOURCE ALLOCATION IN MULTIUSER MULTICARRIER WIRELESS SYSTEMS Ian Wong TheUniversityofTexasatAustin DepartmentofElectricalandComputerEngineering Austin, Texas Brian Evans TheUniversityofTexasatAustin DepartmentofElectricalandComputerEngineering Austin, Texas IanWong BrianEvans TheUniversityofTexasatAustin TheUniversityofTexasatAustin DepartmentofECE DepartmentofECE Austin,TX78712 Austin,TX78712 [email protected] [email protected] LibraryofCongressControlNumber:2007934522 ResourceAllocationinMultiuserMulticarrierWirelessSystems byIanWongandBrianEvans ISBN-13:978-0-387-74944-0 e-ISBN-13:978-0-387-74945-7 Printedonacid-freepaper. (cid:2)c2008SpringerScience+BusinessMedia,LLC. 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Theuseinthispublicationoftradenames,trademarks,servicemarksandsimilarterms,eveniftheyare notidentifiedassuch,isnottobetakenasanexpressionofopinionastowhetherornottheyaresubject toproprietaryrights. 9 8 7 6 5 4 3 2 1 springer.com For our lovely wives, Lynn and Mouna Preface Next-generation broadband wireless standards, e.g. IEEE 802.16e and Third Generation Partnership Project – Long Term Evolution (3GPP-LTE), use Orthogonal Frequency Division Multiple Access (OFDMA) as the preferred physicallayermultipleaccessscheme,esp.forthedownlink.Duetothelimited resources available at the base station, e.g. bandwidth and power, intelligent allocation of these resources to the users is crucial for delivering the best possible quality of service (QoS) to the consumer with the least cost. The problem of allocating time slots, subcarriers, rates, and power to the different users in an OFDMA system has been an area of active research in recent years. Previous research efforts in OFDMA resource allocation have typicallyfocusedonmaximizinginstantaneousperformance,i.e.theallocation decisions are performed for the current time instant subject to the current resourceconstraints,whichisunabletofullyutilizethetime-varyingnatureof thewirelesschanneltoimprovethecommunicationperformanceofthesystem. This book focuses instead on maximizing time-averaged rates, allowing us to exploit the temporal dimension to improve performance. Furthermore, due to the difficult combinatorial nature of the problem, many researchers in the past have focused on developing sub-optimal heuris- tic algorithms. This book proposes a unified algorithmic framework based on dual optimization techniques that have complexities that are linear in the number of subcarriers and users, and that achieve negligible optimality gapsinstandards-basednumericalsimulations.Adaptivealgorithmsbasedon stochastic approximation techniques are also proposed, which are shown to achieve similar performance with even much lower complexity. Finally, it was assumed in previous work that perfect channel state infor- mation (CSI) is available at the transmitter, which is quite unrealistic due to inevitable channel estimation errors and feedback delay. This book develops algorithmsassumingthatonlyimperfectCSIisavailable,suchthatallocation decisions are made while explicitly considering the error statistics of the CSI. Austin, TX Ian Wong June 2007 Brian Evans Contents 1 Introduction............................................... 1 1.1 Next-generation Wireless Communication Systems........... 2 1.1.1 Evolution of Cellular Standards to 3GPP-LTE ........ 3 1.1.2 Evolution of Broadband Access Standards to IEEE 802.16e .......................................... 6 1.2 Orthogonal Frequency Division Multiple Access ............. 8 1.2.1 Overview of OFDM................................ 9 1.2.2 Overview of OFDMA .............................. 10 1.3 Summary............................................... 12 1.3.1 Thesis Statement.................................. 12 1.3.2 Contributions..................................... 13 1.3.3 Organization...................................... 14 1.4 Nomenclature........................................... 14 2 Background ............................................... 17 2.1 Introduction ............................................ 17 2.2 Review of Related Work.................................. 17 2.2.1 Scheduling in Wireless Networks .................... 17 2.2.2 Multiuser Information Theory....................... 18 2.2.3 Physical Layer (PHY) Transmit Optimization......... 18 2.2.4 PHY-MAC Cross-layer Optimization................. 21 2.2.5 Comparison of Related Work ....................... 21 2.3 A New Approach to OFDMA Resource Allocation ........... 22 2.4 System Model........................................... 24 2.4.1 OFDMA Signal Model ............................. 24 2.4.2 Multiuser Statistical Fading Channel Model .......... 24 2.4.3 Optimization Variables............................. 27 2.4.4 PHY-MAC Interaction ............................. 29 2.5 Conclusion ............................................. 29 X Contents 3 Weighted-sum rate Maximization with Perfect CSI ........ 31 3.1 Introduction ............................................ 31 3.2 Continuous Rate Maximization with perfect CSI and CDI .... 31 3.2.1 Problem Formulation .............................. 31 3.2.2 Dual Optimization Framework ...................... 33 3.2.3 Numerical Evaluation of the Expected Dual .......... 36 3.2.4 Optimal Subcarrier and Power Allocation ............ 37 3.2.5 Complexity Analysis............................... 38 3.2.6 Instantaneous Weighted Sum Rate Maximization ...... 38 3.2.7 constant power Allocation .......................... 41 3.2.8 Analysis of the Duality Gap ........................ 41 3.3 Discrete Rate Maximization with perfect CSI and CDI ....... 46 3.3.1 Problem Formulation .............................. 46 3.3.2 Dual Optimization Framework ...................... 46 3.3.3 Numerical Evaluation of the Expected Dual .......... 48 3.3.4 OptimalDiscreteRate,Subcarrier,andPowerAllocation 49 3.4 Numerical Results ....................................... 50 3.4.1 Continuous Rate Allocation......................... 51 3.4.2 Discrete Rate Allocation ........................... 54 3.4.3 Complexity Comparison............................ 56 3.5 Conclusion ............................................. 57 4 Weighted-Sum Rate Maximization with Partial CSI ....... 59 4.1 Introduction ............................................ 59 4.2 Partial Channel State Information Model................... 60 4.3 Continuous Rate Maximization with Partial CSI and CDI .... 62 4.3.1 Problem Formulation .............................. 62 4.3.2 Dual Optimization Framework ...................... 63 4.3.3 Power Allocation Function Approximation............ 64 4.3.4 Optimal Subcarrier and Power Allocation ............ 65 4.3.5 Complexity Analysis............................... 66 4.4 Discrete Rate Maximization with Partial CSI and CDI ....... 66 4.4.1 Closed-form average BER function .................. 67 4.4.2 Closed-form power allocation function................ 68 4.4.3 Closed-form average rate function ................... 68 4.4.4 Problem Formulation .............................. 69 4.4.5 Dual Optimization Framework ...................... 70 4.4.6 Complexity Analysis............................... 71 4.5 Numerical Results ....................................... 72 4.5.1 Continuous Rate Case ............................. 72 4.5.2 Discrete Rate Case ................................ 72 4.5.3 Complexity Comparison............................ 76 4.6 Conclusion ............................................. 76 Contents XI 5 Rate Maximization with Proportional Rate Constraints ... 79 5.1 Introduction ............................................ 79 5.2 Proportional Rate Maximization with Perfect CSI and CDI... 80 5.2.1 Problem Formulation .............................. 80 5.2.2 Dual Optimization Framework ...................... 81 5.2.3 Computation of the Per-user Ergodic Rate............ 83 5.2.4 Complexity Analysis............................... 85 5.2.5 Extension to Discrete Rates and/or Imperfect CSI..... 85 5.3 Adaptive algorithms for Rate Maximization without CDI..... 85 5.3.1 Overview of Stochastic Approximation ............... 85 5.3.2 Stochastic Approximation Solution to the Dual Problem 86 5.3.3 Proof of Convergence .............................. 88 5.3.4 Complexity Analysis............................... 90 5.3.5 Extension to Other Formulations .................... 90 5.4 Results and Discussion ................................... 91 5.5 Conclusion ............................................. 93 6 Conclusion ................................................ 95 6.1 Summary............................................... 95 6.2 Future Work............................................ 97 6.2.1 Other Formulations................................ 97 6.2.2 MAC-PHY Cross-layer Scheduling................... 99 6.2.3 MIMO-OFDMA................................... 99 6.2.4 Multi-cell OFDMA ................................ 99 6.2.5 Multi-hop OFDMA................................100 A Derivation of the inverse function (3.10) of g (3.8) .......101 m,k B Proof of Prop. 3.1 .........................................103 C Derivation of (3.35) ........................................105 D Derivation of the cdf (3.39) and pdf (3.40) of gd (3.38) ....107 m,k E Derivation of (4.30) ........................................109 References.....................................................111 Index..........................................................117 List of Tables 1.1 Wireless data applications and their required data rates [1] .... 2 1.2 IEEE 802.16e OFDMA Scalability Parameters [2] ............ 8 2.1 Related work comparison.................................. 22 2.2 Notation Glossary ........................................ 25 3.1 Simulation Parameters .................................... 51 3.2 Relevant Performance Measures for the Continuous Rate Resource Allocation Algorithms ............................ 54 3.3 Relevant Performance Measures for the Discrete Rate Resource Allocation Algorithms ............................ 56 3.4 Comparison of the proposed ergodic and instantaneous rate resource allocation algorithms with constant power allocation algorithm assuming perfect CSI and CDI. ................... 57 4.1 Comparison of the proposed continuous and discrete rate resource allocation algorithms assuming partial CSI, with the suboptimal method of using the perfect CSI algorithms on the imperfect CSI. ........................................... 71 4.2 Simulation Parameters .................................... 72 4.3 Relevant Performance Measures for the Proposed Resource Allocation Algorithms .................................... 74 6.1 Comparison of proposed algorithms with previous work ....... 96
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